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Existence and consequences of dormant features

Evidence from L2 acquisition of Chinese object ellipsis

Bibliographic Data

ID11656197
AuthorsLulu Zhang (0000-0003-2191-0663, Fudan University, corresponding author)
Year2021
Volume39
Issue3
Pages649-666
Publication date2021-12-29
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSecond language Research (JOURNAL)
Journal identifiersISSN: 0267-6583 • E-ISSN: 1477-0326
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1177/02676583211066293
OpenAlexW4200383917
LanguageEN
References cited16

The current study investigates second language acquisition of Chinese object ellipsis to probe the development of features transferred from learners’ native language without robust confirming or disconfirming evidence in the second language (L2) input. It is argued that Chinese allows object ellipsis licensed by a verb with a [V Case ] feature but not by a verb with a [V non-Case ] feature. In contrast, Korean allows object ellipsis to be licensed by both types of verbs, whilst English prohibits both. An acceptability judgement task was conducted among first language (L1) English and L1 Korean L2 Chinese learners from elementary to advanced levels, with the results showing that the [V non-Case ] feature was assembled in the Chinese grammars of English and Korean elementary L2 learners; however, it gradually lost its vigour and licensing power for object ellipsis in intermediate L2 grammars and was successfully removed from licensing object ellipsis in advanced L2 grammars. These findings support predictions by Yuan regarding a feature’s dormant status and modify Yuan’s predictions regarding a dormant feature’s consequences

Ellipsis (linguistics · Feature (linguistics · Judgement · Linguistics · Modal verb · Natural language processing · Object (grammar · Rule-based machine translation · Second-language acquisition · Verb · Verb phrase ellipsis · Computer Science · Natural Language Processing Techniques · Philosophy · Psychology · Speech and dialogue systems · Syntax, Semantics, Linguistic Variation · Artificial Intelligence

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